Analysis of activity in fMRI data for multitask experimental paradigm using affinity propagation clustering

Clustering analysis is a promising data-driven method for the analysis of functional magnetic resonance imaging (fMRI) data. We use affinity propagation clustering (APC), a new clustering algorithm especially for large data sets, to detect brain functional activation from fMRI in multitask experimental paradigm. The real fMRI study reveals that brain functional activation can be effectively detected and that different response patterns can be distinguished using this method.